This capstone course is a field-based internship designed to develop and hone the practical application skills of an Applied Psychology major. The course requires students to integrate the knowledge and skills gained from other courses in the program and to demonstrate the ability to apply their knowledge to new subject matter and practical situations. Students apply for an internship at a self-selected site and negotiate the terms of the internship experience with a site supervisor under the auspices of their faculty mentor. The internship requires documented evidence of eighty hours of supervised experience and practice in a field setting where psychology-related knowledge and skills are applied. NOTE: Registration for this course, an internship, is by permission of Academic Affairs. Early registration deadlines may apply. Prior to capstone enrollment, students are expected to complete the majority of their required major courses. Students should consult with their advisor regarding specific major courses that may be completed with their capstone. Academic Advisor approval is required for registration to be processed. NOTE: Students who were admitted to the college before Fall 2019 and have remained active in their original catalog year are not required to take IDIS 601.

Lecture and Laboratory introduction to biological principles; cell structure, function, replication, energetics and transport mechanisms; physiological processes; Mendelian, molecular genetics and gene technology. Required for students majoring in the life sciences. Special fee. Lab.

Lecture and laboratory survey of the five kingdoms of life; physiology of cells, tissues, organs, and organ systems; evolution; human impact on the biosphere. Required for students majoring in the life sciences. Cannot be taken for credit after BIOL 412 or equivalent. Special fee. Lab.

Knowledge of biostatistics is essential to understanding our observations of life on Earth and properly design and conduct scientific research. Students develop skills in organizing data and performing, presenting, and interpreting statistical analyses. Theoretical concepts are applied using statistical software(s) and prepared biological data. Topics include descriptive statistics, continuous and discrete probability distributions, inferential statistics, confidence intervals, hypothesis testing for a difference of means and proportions, linear regression, non-parametric hypothesis testing, and graphing.